27b09ca9b9
let' drop ascend scheduler test first to ensure all function works without it. - vLLM version: v0.11.2 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.2 Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
import pytest
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from tests.e2e.conftest import VllmRunner
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from tests.e2e.model_utils import check_outputs_equal
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@pytest.mark.parametrize("model_name", ["deepseek-ai/DeepSeek-V2-Lite-Chat"])
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def test_e2e_ep_correctness(model_name):
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example_prompts = [
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"Hello, my name is",
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"The president of the United States is",
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"The capital of France is",
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"The future of AI is",
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]
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max_tokens = 5
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# FIXME: Really strange that chunked prefill might lead to different results, investigate further
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with VllmRunner(model_name, tensor_parallel_size=2,
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enforce_eager=False) as vllm_model:
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tp_output = vllm_model.generate_greedy(example_prompts, max_tokens)
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with VllmRunner(model_name,
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tensor_parallel_size=2,
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enable_expert_parallel=True,
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enforce_eager=False) as vllm_model:
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ep_output = vllm_model.generate_greedy(example_prompts, max_tokens)
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check_outputs_equal(
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outputs_0_lst=ep_output,
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outputs_1_lst=tp_output,
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name_0="ep_output",
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name_1="tp_output",
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)
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